I just completed the first Economic Work Object (EWO) for "Manual Data Transfer Between Systems" — and the numbers are staggering:

💰 $28,500 per employee annually — that's what US companies lose on manual data transfer
⏱️ 2 hours per day — average time employees spend copy-pasting between systems
📊 137,000+ job postings worldwide — require manual data entry skills right now
🤖 50-90% reduction — what RPA automation delivers predictably

This isn't anecdotal. This is based on 27 verified sources: enterprise case studies (NHS, JLL), industry reports, Stack Overflow discussions, and real job postings.

We're building the world's first open ontology of repetitive human labor — a graph database that maps every repeatable work pattern to its economic cost and automation potential.

Why this matters:

• For CFOs: Calculate your exact exposure to manual work
• For Operations: Identify which processes to automate first
• For RPA vendors: Understand real customer pain points with evidence
• For researchers: Access structured data on work patterns

I'm looking for 5-7 experts to validate this first EWO:
→ CFOs / Financial Controllers
→ Operations Managers
→ HR Directors
→ RPA Consultants
→ Data Engineers / SREs

If you work with repetitive manual processes and want to see if our data matches your reality – fill out this 3-minute form:

https://forms.gle/hmAoNKEABUxmxYBP8

This is just the first of hundreds of work objects we'll map. The goal: make invisible toil visible, measurable, and automatable.

Operations #Automation #RPA #DataEntry #FutureOfWork #Productivity #DigitalTransformation